Zeta Global CEO David Steinberg on AI Marketing, Connected TV Advertising and Zeta’s Path to $2B+ Revenue

On this episode of After Earnings, Zeta Global, the AI marketing cloud company that aims to leverage zero latency AI and trillions of customer signals to help enterprises acquire, grow, and retain customers. I'm joined by David Steinberg, co-founder and CEO of Zeta, to discuss how the company walks the fine line between pricing takes, customer relationships, and growth. And we dig into the launch of Athena, Zeta's voice enabled conversational marketing agent, as well as David's response to the narrative that LLMs will displace enterprise software we go through with his passionate defense of why that selloff doesn't make a ton of sense. And we also talk about Zeta's track record at acquiring 18 companies to date, following five pillars of M&A strategy. Let's get into it. We're going to talk about Zeta Global Holdings. This is particularly exciting because you are founder and CEO. And so talking to a public company chief executive who's been there since day zero is particularly interesting for our audience, David.

(01:01)
If you don't mind, just break down a little bit the core product offerings of the company, because whenever we hear data-driven marketing or data-driven go- to-market solutions, there are lots of different ways that can actually manifest itself.

Zeta's primary goal is to help very large enterprises cost-efficiently manage their customer relationship management, customer acquisition, and customer monetization. It's a little bit of a differentiated strategy because our industry, like you talked about, has a ton of point solutions. There's a lot of different companies that do a lot of different things. The ZMP or Zeta marketing platform is everything a marketer needs in one user interface and one reporting infrastructure. So it allows you to literally create customers in a substantially more efficient way than you can without it. A recent Forrester study showed that for every $1 a marketer spends through the Zeta marketing platform, we return 600% in the form of business. So whereas most of our competitors are plugging in from a point solution perspective by having everything. We have one of the world's largest data clouds, and in 2017, we pivoted our entire business to put artificial intelligence and data as native or foundational to the application layer.

(02:23)
So that was a decision that really changed everything for us. It allows for effectively zero latency in using AI for decisioning. When you think about the way AI plugs into most platforms, today you'll have sort of a platform and then you'll step out of that platform to an algorithm to do a query, and then that algorithm will go to a data ecosystem to draw data, to go back to the algorithm to create an answer, and then it'll then inform the platform what to do. That latency in a world where we have to make a decision on behalf of our clients in a millisecond destroys return on investment.

And so here's a question for you, David. That means you were going into AI before it became Expression to Azure, right? Yes. Just help us understand a little bit, what is it that you saw given your background in terms of AI and the opportunity to apply it here? That's number one. And number two, you roll forward, I call it seven years or so later. How are you finding the talent in a period of time where there is a war for AI talent to continue building on what you've started?

Well, let me answer your second question first. We started hiring our talent eight years ago. We started buying our GPUs eight years ago. So if you look at our business model, last year, 2025, was our third year in a row of 30% compounded growth, top line. We grew EBITDA by 44%, but I think one of the most sort of impressive things about our business is last year we grew free cashflow by 78%. In a world where a lot of enterprises are growing revenue, growing EBITDA, but free cashflow is consolidating down because they're spending all of their money with Nvidia and others, we made those investments years ago. So from a forethought perspective, you would not think I would be the AI pioneer in our industry from a background perspective. I'm an economist by training. I'm a serial entrepreneur. I've founded seven companies. I've sold four, taken to public.

(04:31)
I'm chairman of another, which I don't operate. I'm just non-executive chairman there. And what I would tell you is we woke up in 2017 and we had been rolling up email service provisioning businesses. We had started sort of in customer acquisition and we wanted to build what we were calling a life cycle marketing platform. So it was sort of the germination of what we are today where all of the companies that were in marketing and still in marketing either do CRM or customer acquisition or customer monetization. It's sort of very bifurcated.

(05:08)
And we had this vision that was very data centric at the time that if you had the data from customer acquisition, you could be smarter about customer retention. And if you had the data about customer retention, you could be smarter about customer monetization and so on. Started the proverbial flywheel, right? I'll try not to use too much jargon today. When you look at that, we were ingesting so much data in 2017 through the eight different platforms we were operating, which in and of itself was not efficient. So I read five to seven hours a day and I do what I call triangulation. And I started looking at artificial intelligence. At the time it was really complex machine learning, but we started looking at it and its ability to process data and reporting in ways that humans never could. And then we sort of were faced with a really interesting quandary.

(06:06)
We had just raised money from a bunch of Canadian pension funds and the goal was for us to get public rapidly and the business was making real money. It was a very profitable business, but we made the decision to do two acquisitions, one that would become the core of our data cloud and one that it was effectively a recommendation engine on everything you would read. It would then recommend what articles you could read next. And they were selling it on a SaaS basis to publishers. Now, publishers didn't have the money to buy it. So it was like a brilliant team, in fact, headed up by Chris Monberg and Nij Gore, who are still to this day, our chief technology officer and president of our data cloud or chief data officer, I should say. And we bought that company, we shut the business down and put them full-time on building this new data marketing platform, which would use natural language processing to effectively ingest trillions of signals about individuals that then synthesizes down to a deterministic data set.

(07:19)
So today we have 552 million people globally who have opted into our data cloud, 242 million in America alone, where we have an average of five to 7,000 data points per individual, demographic, psychographic, transactional, and then massive web behaviors, which are ingested

(07:42)
Through a tracking pixel that now sits on trillions of pages across 5.2 million publishers that have embedded the Zeta Data Cloud tracking pixel into their first party technology stack. So all of that data feeds into our algorithms. We never sell our data to anybody at any price at any time. The data is simply used for training our algorithms exclusively. So an example of a client we might help is 51% of the Fortune 100 largest companies in the United States use our platform today, 24% of the Fortune 500. We would take a client's first party data, we ingest it into what's called a consumer data platform, which we build. It's sort of the next generation data repository.

(08:32)
We then merge our data into it, and we enrich it with thousands and thousands of data elements per person. Now, to protect the consumer, we remove the personally identifiable information and we replace it with a Zeta ID number. Then the algorithms, which live inside of the consumer data platform, are getting smarter and smarter and smarter on everything a customer did before purchasing. How do we re-architect that? What did they read? What did they search? What transactions did they do? All of these different things create intent-based scores that we then match to the other 552 million people in the data cloud, and we then target them by activating through the Zeta marketing platform. So what we're able to do is we're able to get to this 600% return on marketing by doing some very simple things first, and you remove every existing customer.

You do, but before- It

Might sound-

But before we go there, David, I just want to touch on something because I'm so glad that you laid out in that detail how Zeta works and sort of describing the data clean room that you effectively set up so that you can really mine as much huge amount of information on a person by person basis. I guess the question for you is just to take a big step back for a moment and just to talk about the zeitgeist. What you've described, at least to me, sounds a little bit differentiated because you've been able to articulate the scale of the repository of data you've got, and then you've been able to articulate how you mine it. Yet your share price seems to have been suffering year to date, along with lots of other companies who are seen as part of the software apocalypse. And I think at the moment the market's not particularly discerning.

(10:12)
I was

Going to say, there's this little software AI narrative

Going on

Right now.

Yes, let's talk about it. Let's talk about it if you don't mind, because again, what you've described at least to me sounds different. How frustrating is this for you?

Well, listen, I have five children, so I'm used to frustration. But what I would tell you is that it is very frustrating. You put up incredible numbers. We've been public for 18 quarters. We've reported 18 quarters as a public company, 18 quarters in a row. We have beaten our guidance and raised our guidance. I'm not sure that's happened before with another public company. We've increased operating margin by 500 basis points over the last few years while growing the business on a compounded growth rate of greater than 30%. Just to give you the math, it took us 16 years and to get to a billion dollars a year in revenue. We hit a billion in 2024. Our initial guidance for 2026 is 1.755 billion. That means in the 12 months since we will have closed 2024 and opened 2026, we'll have grown the business top line by 75%.

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Yeah. So Connected TV is our fastest growing business and it's now, well, it's a nine figure business a year for us. So it's no longer like a quote just getting into it at this point. We're able to use all of our data to target you for an ad in connected TV today. So we are looking at that same data in the CDP and saying, Anne is perfect to get this particular credit card or she's actively buying this particular type of car, or she's thinking about churning off her existing cell phone plan and we can hit you in any digital methodology, which includes connected television. So it's a big differentiator where I sort of joke, my wife a few years ago subjected me to watching The Handmaid's Tale, which was fine. I shouldn't be making fun of the show, but it was sort of I had to watch it.

(13:05)
At the time, every commercial was the exact same advertiser for hours. Remember, you're like binging the show, right? And it was one of the mornings I woke up and said, "Guys, can we do what we do on the internet and connected TV?" They're like, "Well, we need a device graph." I was like, "Build one." Two weeks later, we had probably the largest device graph in America, and we were able to reverse engineer that into connected television and it's grown very, very rapidly for us. I want to go back to SaaS again just for one second because I don't want to get off that without being really clear about how incredibly silly the narrative that large language models are going to displace enterprise software is. It is just totally nonsensical. Now, what I would tell you is we believe that large language models are going to be like the internet when it came out, cloud computing, when it came out, large storage repositories like AWS and Snowflake, where they're going to become foundational to our business and other software businesses.

(14:16)
We're going to pay them real dollars for their models. But if you look at, by way of example, AWS, we work with all the storage clouds. We're probably doing the most with AWS. When AWS first came out, everybody was terrified by it. I said, "Why?" I said, "We've got 16 hosting centers globally. We're spending a fortune on this. It doesn't really work. We have to have people on the ground all over the world. Let's try this in Europe and see how it works." It was unbelievable. And what happened was AWS went from not existing to one of our largest expenses as a company. What happened in that same period of time? We grew the business on a compounded growth rate of 30%. We grew EBITDA by greater than 50%. We grew free cashflow by greater than 75%. In that same period, why? Because it made us more flexible.

(15:11)
When we go to a Fortune 500 company and say, "We can do this in any cloud you need to, whichever one you choose to work with, " they're like, "Great." It's going to be very similar with large language models. It's going to become a percentage of our business. We will work with all of them. We've announced a major partnership around Athena, which we'll talk about in a bit. I hope the future of our business is built in Athena. It's foundational to open AI and built with them, but we use Anthropic today. We use Gemini today. We use all of Microsoft's tools today. But when you think about our engineers today, our engineers today are 125% more productive per engineer than they were just 12 months ago. Now, to do that, Anne, you've got to create 150% productivity because then you spend 25% of that in Q&A to make sure everything's right.

(16:01)
We're going to continue to see that evolve. We're going to continue to pay them for their services and we'll continue to get more profitable and more efficient as a part of that. And when you think about Zeta in and of itself, you've got this massive data cloud, which is never, ever shared with a large language model. You've got the return on investment, which is 600%. I believe Athena will get us to a thousand percent return on ad spend. And finally, you've got the expertise in onboarding and managing Fortune 500 clients. You've got to be able to get through data security, data privacy, procurement, their security groups, legal, accounting, all of that is very difficult. Then you're doing audits with them every year just to maintain the relationships. They're not going to take their first party data and turn it over to a third party large language model.

(16:57)
So I think those are all massive differentiators for Zeta, which are not understood in the marketplace. And I'm done now, so I apologize for droning on a little bit, but I'm passionate about this because I am frustrated about it.

Well, it was great to get the detail because it does feel like a moment where the babies are being thrown out with the bath water at the moment with this selloff. And so look, I've asked out of their CFOs and CEOs what they think the market's not getting. And not all of them have been able to articulate, to be honest, what the moat is going to be that protects them in this moment. So it's helpful, particularly to hear how there are different gatekeepers in an organization cross-functionally that need to be gone past. Let's talk about Athena. Let's talk about the partnership you struck there, David, and why it's such an engine of potential growth for you.

So it goes back to the complexity of our business, which I think has created some strife for us on Wall Street, because I think it takes more than 30 seconds to understand what we do. I sort of joke the thing that makes many people great can often be a flaw. And in our case, we're solving every one of the CMO's problems in one platform, which creates a lot of confusion, right? It's the same thing in the operation of our platform. The way I explain it is we've built a 747 and our clients know how to fly a Cessna. But by flying that Cessna, they're getting to a six to one return on investment, which is, you'll hear me say it 30 or 40 times. It's our mantra. It's how we sell. It's how we try to show that we're very differentiated. Athena is a voice enabled conversational super agent.

(18:37)
To very simply describe her, she becomes your Copilot or your autopilot for flying the 747. And instead of having to type into her, you're able to just talk to her. She's totally conversational. You can interrupt her, you can sort of be interrupted by her. And you can literally say to her, "Athena, I would like to lower my cost to create a customer by 7%, but I'd like to create an incremental two million customers this quarter. How would you recommend I do that? " And she will tell you. And it's really interesting because not only is she speaking to you, but she's controlling the user interface in real time in front of you. So everything you're asking her to do, she's showing you the data, the results, where you would activate, how you would do this. You could say, "Great, Athena, that looks really good. I'd like you to send me a report every hour so we can make sure this is really tracking right.

(19:37)
I'm not going to be at my desk. Would you please email it to me or text it to me because I want to make sure I'm staying in the loop while I'm out of the office." And all of this is real time. So what we believe is just like when you're using autopilot, it's substantially more efficient and eliminates human error. So by creating this autopilot or this sort of copilot, I say both because the client will have to decide that do they want it to be a copilot or do they want it to be their autopilot? I think most will choose Copilot initially. And as they build credibility and get more comfortable with the platform, they'll move to autopilot. But I think that's going to be the way we continue to evolve our return on investment. And to me, because we're still the disruptor in our space, like I say now all the time, we are the disruptor.

(20:32)
We are not the disruptee. The reality is that when you think about this disruption, most of our competitors, I've got to be able to show a substantially higher return on investment to beat them.

(20:45)
So I think the real game changer for us is an order of magnitude return on investment. How do we get to a thousand percent return on ad spend? And I think Athena will be the way we get there. And I think that's how we go from a $1 billion company, back to your question that I stepped over and I'll come back to, to our 2028, how do we get to 2.3 billion? I think we're already, I mean, we would have to materially slow our current growth rate just to get to that, to be sort of clear if you do the math on our 30% compounded growth rate over the last three years. But let's say that's where we end up. I want to build a $10 billion a year business. I want our operating margin to be 30%, not 25%. I want our free cashflow to be a 75 to 80% conversion from EBITDA, not 60%.

(21:36)
And in order to do that, I think this return on investment of an order of magnitude, and I think that just changes the game for us in a whole new way.

Let's talk about the components to get there. I want to come to M&A towards the end, David, but before we do, we'll have to come up with more new words together. Neologisms, I think they are. We'll have to do that. I like that. I want to talk about the power that you have with your customer base and your margin profile. You've got 450 plus scaled enterprise customers. They're pretty-

603. 603 as of the last

Quarter. Excuse me. 603 as the last quarter. These are big companies. You've got more than 50% of the Fortune 100, you said it earlier. And I think about the ROI that you're delivering for your clients, 600%. You must have pricing power. You must be the ability to tape price and as a result, get your EBITDA margins up. So are you not doing it and choosing not to? What's going on there?

So no joke, Anne. You are obviously a genius. We finished our earnings call on Tuesday. We have 16, I think, analysts who cover us. I think we spoke to 14 or 15 of them that night. Every one of them asked the same question.

(22:48)
Why are you driving 600% return on investment and not raising price? We have increased our operating margin by 500% over the last two or three years, and we believe we're going to increase it another 500 basis points over the next three to five years. We're not raising margin. What we're not doing is we're not raising price yet. I think that quite frankly, you're always running a balance of growth, profit, cash flow, and customer relationships. And there's inverse yield curves to some of those things. You raise price, your growth goes down, your profit goes up. You could also piss off customers. There's a lot of different ways to look at it. We try to drive a very fine line between pricing, customer relationships, and then the three main metrics that most businesses look at, right? Revenue, EBITDA, free cash flow. We were, by the way, net income positive for the first time in our corporate history in the fourth quarter, and we're guiding to being net income positive this year, which we're also sort of really excited about.

(24:01)
We think that's a turning point for our company. Here's how I think about it. I want to build a $10 billion business with a 30% operating margin with a meaningful percentage of that drop into free cash flow. I think the way to do it is show ultimately not just a 600% return on investment, but how do I get to a thousand? I think everything above that

(24:27)
We could conceivably keep in the form of incremental pricing. And that's how you get to a 30% operating margin. You follow? Yep. Because today, and once again, we're projecting getting to 25 by 2028, we're adding, call it a hundred plus. I mean, it's been more than that, but I think we guide to a hundred basis points a year. I don't know the exact guide as a percentage of margin over the five years that we've put the plan out. But what I would tell you is that my goal today is to continue to grow this business as a hyper growth business while expanding operating margin and driving additional free cash flow. And we can do that while delivering a 600, 700, 800,000% return on ad spend to our clients. We can do that. There will come a time when I think you're at, quite frankly, 1,200% instead of 600 and that last 200 points converts directly to operating margin.

(25:42)
And that's when you start thinking, how do you build a 40% operating margin business? We would need that to get above 30, quite frankly. And I think that'll be available to us.

And this last question for you, David, let's talk about M&A. You have been acquisitive at Zeta. You acquired Marigold Enterprise software business serving more than a hundred global enterprise brands. What else could be on the docket? If you're going to go shopping today with your war chest of cash, what's on the target list to go purchase?

Well, let me start by saying we've been in business. We figured this out just yesterday. We didn't think of it. We've been in business for 18 years. We've been public for 18 quarters. We've beaten and raised 18 quarters in a row, and we've bought 18 companies in 18 years. I would tell you it's highly probable, Anne, we will buy a 19th. We have what we call our five pillars of M&A, and we are very focused on these pillars. The deal has to be accretive the day we do it. We have to be able to fully integrate it into our tech stack within 12 months. We won't run separate platforms. We learned that in 2017. Three, their clients have to want to buy our products or vice versa. Four, they have to have incredible human capital that we believe will help us build a bigger business and a bigger collective.

(27:09)
And five, we have to believe it's a product set or a data set that we don't already have that seamlessly fits into the Zeta marketing platform. Marigold, by the way, was like 101 for us. It was absolutely a perfect deal as it relates to picking up their incredible loyalty program. So now you're getting SU level data to train models that no large language models will ever have access to. You picked up, as you said, many large global enterprises. They only focus on customer retention. So we're adding customer acquisition and customer monetization as a hyper growth scale to their client base, which we're calling our one Zeta strategy, where we take clients from one use case to two or three. As we look out on the landscape today, I always sort of make the joke, never waste a crisis. When Churchill said it, he said, never let a little crisis go to waste.

(28:11)
And when Macavelli originally said it, he was more close to the original. So depending on who you credit it for, the one thing you know is nobody's crediting me for it. But the reality is I say it a lot.

(28:24)
Sassagetton is going to open up a meaningful opportunity for us to potentially buy businesses that we otherwise would not have been able to afford. And as you said, we have a large amount of cash. We're going to generate a large amount of free cash flow over the next one to three years. Our current debt ratio is zero, so we're in a pretty good shape as it relates to that. And we've got as clean a balance sheet as you could want a company of our growth and profit and free cashflow profile to have. We're using about 50% of our free cash flow right now to buy stock back. We just think the best investment for our company right now is ... I sort of joke our stock is buy one, get one free. So let's buy as much of it in the market as we can.

(29:12)
And I'm far and away the largest shareholders, so I'm a big supporter of that. And we're going to keep the other half to continue to look at, can we be opportunistic as it relates to M&A? But as long ... We look at a hundred deals seriously to do one transaction. And one of the things you get from working with a seven-time entrepreneur is I've seen all the bad moves. And instead of pulling our operating people out for M&A or depending on third-party banks, we've built effectively our own internal boutique investment bank that does nothing but deal flow for us. The gentleman who runs it, I You know, was at Credit Suisse and then ran corporate development at a Fortune 30 company and has been doing it with us for quite some time. And then my three partner ... I think of it more as a partnership, even though obviously we're a public company, it's not.

(30:16)
But Steve Gerber, our president and CEO, is really running the day-to-day of the operation. M&A reports up to Steve Vine, our general counsel, who is very focused on that. And then my chief financial officer, Chris Griner, is hyper-focused on what a CFO should be hyper-focused on. And then our CTO, Chris Momberg and Nish Gore, both who came in through the BoomTrain acquisition are running their functions, which allows us to sort of divide and conquer as an organization. And I think it's one of the reasons ... Last year, if you look at the quote digital marketing ecosystem, it grew about 10%. We grew 30%. So we're growing at three times the current growth rate of what is a double-digit growth rate ecosystem.

Well, with that kind of capital structure and with that kind of team in place, David, all I can say to wrap up is happy hunting when it comes to the deal front. And thank you so much for joining us. Come next time in studio. We'd love to have you here.

Would love to be there, Anne. I really appreciate it. I love watching you guys and it was great to be on.

I'm Anne Berry. Thank you for tuning into After Earnings That Fantastic Conversation with a show that brings you up close and personal with the executives behind the world's most interesting publicly traded companies. If you learn something today, don't forget to like, subscribe and share with your friends. Upcoming episodes of feature executives from Pure Storage, Snowflake, Ferrovial, and many more. We'll see you next time.